Aptamer has been long studied as a substitute of antibodies for many purposes. However, due to the exceeded length of the aptamers obtained in vitro, difficulties arise in its manipulation during its molecular conjugation on the matrix surfaces. Current study focuses on computational improvement for aptamers screening of hepatitis B surface antigen (HBsAg) through optimization of the length sequences obtained from SELEX. Three original aptamers with affinity against HBsAg were truncated into five short hairpin structured aptamers and their affinity against HBsAg was thoroughly studied by molecular docking, molecular dynamics (MD) simulation, and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method. The result shows that truncated aptamers binding on HBsAg "a" determinant region are stabilized by the dynamic H-bond formation between the active binding residues and nucleotides. Amino acids residues with the highest hydrogen bonds hydrogen bond interactions with all five aptamers were determined as the active binding residues and further characterized. The computational prediction of complexes binding will include validations through experimental assays in future studies. Current study will improve the current in vitro aptamers by minimizing the aptamer length for its easy manipulation.
Ebola virus is a lipid-enveloped filamentous virus that affects human and non-human primates and consists of several types of protein: nucleoprotein, VP30, VP35, L protein, VP40, VP24, and transmembrane glycoprotein. Among the Ebola virus proteins, its matrix protein VP40 is abundantly expressed during infection and plays a number of critical roles in oligomerization, budding and egress from the host cell. VP40 exists predominantly as a monomer at the inner leaflet of the plasma membrane, and has been suggested to interact with negatively charged lipids such as phosphatidylinositol 4,5-bisphosphate (PIP2) and phosphatidylserine (PS) via its cationic patch. The hydrophobic loop at the C-terminal domain has also been shown to be important in the interaction between the VP40 and the membrane. However, details of the molecular mechanisms underpinning their interactions are not fully understood. This study aimed at investigating the effects of mutation in the cationic patch and hydrophobic loop on the interaction between the VP40 monomer and the plasma membrane using coarse-grained molecular dynamics simulation (CGMD). Our simulations revealed that the interaction between VP40 and the plasma membrane is mediated by the cationic patch residues. This led to the clustering of PIP2 around the protein in the inner leaflet as a result of interactions between some cationic residues including R52, K127, K221, K224, K225, K256, K270, K274, K275 and K279 and PIP2 lipids via electrostatic interactions. Mutation of the cationic patch or hydrophobic loop amino acids caused the protein to bind at the inner leaflet of the plasma membrane in a different orientation, where no significant clustering of PIP2 was observed around the mutated protein. This study provides basic understanding of the interaction of the VP40 monomer and its mutants with the plasma membrane.
Literature has shown that oil palm leaves (OPL) can be transformed into nanocellulose (NC) by fungal lignocellulosic enzymes, particularly those produced by the Trichoderma species. However, mechanism of β-glucosidase and xylanase selectivity to degrade lignin, hemicellulose and cellulose in OPL for NC production remains relatively vague. The study aimed to comprehend this aspect by an in silico approach of molecular docking, molecular dynamics (MD) simulation and Molecular-mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis, to compare interactions between the β-glucosidase- and xylanase from Trichoderma asperellum UC1 in complex with each substrate. Molecular docking of the enzyme-substrate complex showed residues Glu165-Asp226-Glu423 and Arg155-Glu210-Ser160 being the likely catalytic residues of β-glucosidase and xylanase, respectively. The binding affinity of β-glucosidase for the substrates are as follows: cellulose (-8.1 kcal mol-1) > lignin (-7.9 kcal mol-1) > hemicellulose (-7.8 kcal mol-1), whereas, xylanase showed a corresponding preference for; hemicellulose (-6.7 kcal mol-1) > cellulose (-5.8 kcal mol-1) > lignin (-5.7 kcal mol-1). Selectivity of both enzymes was reiterated by MD simulations where interactions between β-glucosidase-cellulose and xylanase-hemicellulose were the strongest. Notably low free-binding energy (ΔGbind) of β-glucosidase and xylanase in complex with cellulose (-207.23 +/- 47.13 kJ/mol) and hemicellulose (-131.48 +/- 24.57 kJ/mol) were observed, respectively. The findings thus successfully identified the cellulose component selectivity of the polymer-acting β-glucosidase and xylanase of T. asperellum UC1.Communicated by Ramaswamy H. Sarma.
Recent outbreaks of highly pathogenic influenza strains have highlighted the need to develop new anti-influenza drugs. Here, we report an in silico study of carvone derivatives to analyze their binding modes with neuraminidase (NA) active sites. Two proposed carvone analogues, CV(A) and CV(B), with 36 designed ligands were predicted to inhibit NA (PDB ID: 3TI6) using molecular docking. The design is based on structural resemblance with the commercial inhibitor, oseltamivir (OTV), ligand polarity, and amino acid residues in the NA active sites. Docking simulations revealed that ligand A18 has the lowest energy binding (∆Gbind) value of -8.30 kcal mol-1, comparable to OTV with ∆Gbind of -8.72 kcal mol-1. A18 formed seven hydrogen bonds (H-bonds) at residues Arg292, Arg371, Asp151, Trp178, Glu227, and Tyr406, while eight H-bonds were formed by OTV with amino acids Arg118, Arg292, Arg371, Glu119, Asp151, and Arg152. Molecular dynamics (MD) simulation was conducted to compare the stability between ligand A18 and OTV with NA. Our simulation study showed that the A18-NA complex is as stable as the OTV-NA complex during the MD simulation of 50 ns through the analysis of RMSD, RMSF, total energy, hydrogen bonding, and MM/PBSA free energy calculations.
Being commonly found at crime scenes, fingerprints are crucial for human identification, attributable to their uniqueness, persistence and systematic classification of ridge patterns. In addition to latent fingerprints being invisible to the naked eye, the escalating trends of disposing forensic evidence bearing such prints in watery bodies would further complicate criminal investigations. Taking into account the toxicity of small particle reagent (SPR) commonly used in visualising latent fingerprints on wet and non-porous objects, a greener alternative using the nanobio-based reagent (NBR) has been suggested. However, NBR only applies to white and/or relatively light-coloured objects. Thus, conjugation of sodium fluorescein dye with NBR (f-NBR) may be beneficial for increasing the contrast of fingerprint on multi-colored objects. Hence, this study was aimed at investigating the possibility of such conjugation (i.e., f-NBR) as well as proposing suitable interactions between the f-NBR and lipid constituents of fingerprints (tetra-, hexa- and octadecanoic acids) via molecular docking and molecular dynamics simulations. The binding energies between CRL with its ligands were observed at -8.1, -5.0, -4.9 and -3.6 kcal/mole for sodium fluorescein, tetra-, hexa- and octadecanoic acids, respectively. Besides, the formations of hydrogen bonds observed in all complexes (ranged between 2.6 and 3.4 Å), further supported by the stabilized root mean square deviation (RMSDs) plots in MD simulations. In short, the conjugation of f-NBR was computationally feasible, and thereby merits further investigations in the laboratory.Communicated by Ramaswamy H. Sarma.
The data presented here is the liquid chromatography and mass spectrometry (LC-MS) profile of phytochemical compounds in the aqueous extract of Syzygium polyanthum (Wight) Walp. leaves. This plant is consumed raw and sometimes added to local dishes of people in Southeast Asia countries. Most importantly, it has ethnomedicinal values mainly in treating diabetes and hypertension, and at the same time, this plant has anti-microbial, anti-oxidant, anti-cancer, and anti-tumor properties [1]. There are chemical composition variations reported between the same species of different geographical locations, which eventually affect the plant's therapeutic potential [2], [3]. This dataset represents the identified compounds for S. polyanthum (Wight) Walp. leaves, a variant collected from Kuantan, a city located in the Pahang state on the East Coast of Peninsular Malaysia. The leaves were then dried in an open-air at room temperature for three weeks, ground, and then macerated in water inside a bath-sonicator, freeze-dried, and then run using LCMS. The LCMS was run using the ultra-performance liquid chromatography equipped with an electrospray time-of-flight mass spectrometer detector, operated in a negative-ion mode. The mass spectral features from samples raw data were matched with Traditional Medicine (en) and Waters Screening libraries in the Waters UNIFI™ Scientific Information System software version 1.7 (Waters, USA) for compounds identification.
Dehalogenase E (DehE) is a non-stereospecific enzyme produced by the soil bacterium, Rhizobium sp. RC1. Till now, the catalytic mechanism of DehE remains unclear although several literature concerning its structure and function are available. Since DehE is non-stereospecific, the enzyme was hypothesized to follow a 'direct attack mechanism' for the catalytic breakdown of a haloacid. For a molecular insight, the DehE modelled structure was docked in silico with the substrate 2-chloropropionic acid (2CP) in the active site. The ideal position of DehE residues that allowed a direct attack mechanism was then assessed via molecular dynamics (MD) simulation. It was revealed that the essential catalytic water was hydrogen bonded to the 'water-bearer', Asn114, at a relatively constant distance of ∼2.0 Å after 50 ns. The same water molecule was also closely sited to the catalytic Asp189 at an average distance of ∼2.0 Å, signifying the imperative role of the latter to initiate proton abstraction for water activation. This reaction was crucial to promote a direct attack on the α-carbon of 2CP to eject the halide ion. The water molecule was oriented favourably towards the α-carbon of 2CP at an angle of ∼75°, mirrored by the formation of stable enzyme-substrate orientations throughout the simulation. The data therefore substantiated that the degradation of a haloacid by DehE followed a 'direct attack mechanism'. Hence, this study offers valuable information into future advancements in the engineering of haloacid dehalogenases with improved activity and selectivity, as well as functionality in solvents other than water.
Improving forecasting particularly time series forecasting accuracy, efficiency and precisely become crucial for the authorities to forecast, monitor, and prevent the COVID-19 cases so that its spread can be controlled more effectively. However, the results obtained from prediction models are inaccurate, imprecise as well as inefficient due to linear and non-linear patterns exist in the data set, respectively. Therefore, to produce more accurate and efficient COVID-19 prediction value that is closer to the true COVID-19 value, a hybrid approach has been implemented. Thus, aims of this study is (1) to propose a hybrid ARIMA-SVM model to produce better forecasting results. (2) to investigate in terms of the performance of the proposed models and percentage improvement against ARIMA and SVM models. statistical measurements such as MSE, RMSE, MAE, and MAPE then conducted to verify that the proposed models are better than ARIMA and SVM models. Empirical results with three real datasets of well-known cases of COVID-19 in Malaysia show that, compared to the ARIMA and SVM models, the proposed model generates the smallest MSE, RMSE, MAE and MAPE values for the training and testing datasets, means that the predicted value from the proposed model is closer to the actual value. These results prove that the proposed model can generate estimated values more accurately and efficiently. As compared to ARIMA and SVM, our proposed models perform much better in terms of error reduction percentages for all datasets. This is demonstrated by the maximum scores of 73.12%, 74.6%, 90.38%, and 68.99% in the MAE, MAPE, MSE, and RMSE, respectively. Therefore, the proposed model can be the best and effective way to improve prediction performance with a higher level of accuracy and efficiency in predicting cases of COVID-19.
Honey is a sustainable nutritious substance which has been incorporated into the human diet since ancient times for its health and remedial benefits. Stingless bee honey or kelulut honey (KH) is well-known in Malaysia and has received high demand in the market due to its distinctive unique flavour. Its composition, colour, and flavour are majorly affected by the geographical location, floral source, climate, as well as the bee species. This data article presents the nontargeted metabolite profiling of the extracts of KH of Heterotrigona itama and Tetrigona binghami bee species. The KH was collected from three nests in Kuantan, Pahang, which is situated in the east coast of Peninsular Malaysia. The extracts were prepared using sugaring-out assisted liquid-liquid extraction (SULLE) method and the Liquid Chromatography-Tandem Mass Spectrometry with Quadrupole Time-of-Flight, operated in the negative ion mode, was used to identify compounds in the extracts. The data processing revealed the presence of 35 known compounds in the KH1 extract by Heterotrigona itama collected from Bukit Kuin, 38 compounds in the KH2 extract by H. itama collected from Indera Mahkota, whilst 50 known compounds were present in KH3 extract by Tetrigona binghami species from Indera Mahkota. This data article contains the m/z values, retention times, and the METLIN database search hit identities of the compounds and their respective classes.
The human angiotensin-converting enzyme 2 (ACE-2) receptor is a metalloenzyme that plays an important role in regulating blood pressure by modulating angiotensin II. This receptor facilitates SARS-CoV-2 entry into human cells via receptor-mediated endocytosis, causing the global COVID-19 pandemic and a major health crisis. Kelulut honey (KH), one of Malaysian honey recently gained attention for its distinct flavour and taste while having many nutritional and medicinal properties. Recent study demonstrates the antiviral potential of KH against SARS-CoV-2 by inhibiting ACE-2 in vitro, but the bioactive compound pertaining to the ACE-2 inhibition is yet unknown. An ensemble docking-based virtual screening was employed to screen the phytochemical compounds from KH with high binding affinity against the 10 best representative structures of ACE-2 that mostly formed from MD simulation. From 110 phytochemicals previously identified in KH, 27 compounds passed the ADMET analysis and proceeded to docking. Among the docked compound, SDC and FMN consistently exhibited strong binding to ACE-2's active site (-9.719 and -9.473 kcal/mol) and allosteric site (-7.305 and -7.464 kcal/mol) as compared to potent ACE-2 inhibitor, MLN 4760. Detailed trajectory analysis of MD simulation showed stable binding interaction towards active and allosteric sites of ACE-2. KH's compounds show promise in inhibiting SARS-CoV-2 binding to ACE-2 receptors, indicating potential for preventive use or as a supplement to other COVID-19 treatments. Additional research is needed to confirm KH's antiviral effects and its role in SARS-CoV-2 therapy, including prophylaxis and adjuvant treatment with vaccination.Communicated by Ramaswamy H. Sarma.
This study presents the initial structural model of L-haloacid dehalogenase (DehLBHS1) from Bacillus megaterium BHS1, an alkalotolerant bacterium known for its ability to degrade halogenated environmental pollutants. The model provides insights into the structural features of DehLBHS1 and expands our understanding of the enzymatic mechanisms involved in the degradation of these hazardous pollutants. Key amino acid residues (Arg40, Phe59, Asn118, Asn176, and Trp178) in DehLBHS1 were identified to play critical roles in catalysis and molecular recognition of haloalkanoic acid, essential for efficient binding and transformation of haloalkanoic acid molecules. DehLBHS1 was modeled using I-TASSER, yielding a best TM-score of 0.986 and an RMSD of 0.53 Å. Validation of the model using PROCHECK revealed that 89.2% of the residues were located in the most favored region, providing confidence in its structural accuracy. Molecular docking simulations showed that the non-simulated DehLBHS1 preferred 2,2DCP over other substrates, forming one hydrogen bond with Arg40 and exhibiting a minimum energy of -2.5 kJ/mol. The simulated DehLBHS1 exhibited a minimum energy of -4.3 kJ/mol and formed four hydrogen bonds with Arg40, Asn176, Asp9, and Tyr11, further confirming the preference for 2,2DCP. Molecular dynamics simulations supported this preference, based on various metrics, including RMSD, RMSF, gyration, hydrogen bonding, and molecular distance. MM-PBSA calculations showed that the DehLBHS1-2,2-DCP complex had a markedly lower binding energy (-21.363 ± 1.26 kcal/mol) than the DehLBHS1-3CP complex (-14.327 ± 1.738 kcal/mol). This finding has important implications for the substrate specificity and catalytic function of DehLBHS1, particularly in the bioremediation of 2,2-DCP in contaminated alkaline environments. These results provide a detailed view of the molecular interactions between the enzyme and its substrate and may aid in the development of more efficient biocatalytic strategies for the degradation of halogenated compounds.Communicated by Ramaswamy H. Sarma.